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Variation in Performance of Commonly Used Statistical Methods for Estimating Effectiveness of State-Level Opioid Policies on Opioid-Related Mortality

Author

Listed:
  • Beth Ann Griffin
  • Megan S. Schuler
  • Elizabeth A. Stuart
  • Stephen Patrick
  • Elizabeth McNeer
  • Rosanna Smart
  • David Powell
  • Bradley Stein
  • Terry Schell
  • Rosalie Liccardo Pacula

Abstract

Over the last two decades, there has been a surge of opioid-related overdose deaths resulting in a myriad of state policy responses. Researchers have evaluated the effectiveness of such policies using a wide-range of statistical models, each of which requires multiple design choices that can influence the accuracy and precision of the estimated policy effects. This simulation study used real-world data to compare model performance across a range of important statistical constructs to better understand which methods are appropriate for measuring the impacts of state-level opioid policies on opioid-related mortality. Our findings show that many commonly-used methods have very low statistical power to detect a significant policy effect (

Suggested Citation

  • Beth Ann Griffin & Megan S. Schuler & Elizabeth A. Stuart & Stephen Patrick & Elizabeth McNeer & Rosanna Smart & David Powell & Bradley Stein & Terry Schell & Rosalie Liccardo Pacula, 2020. "Variation in Performance of Commonly Used Statistical Methods for Estimating Effectiveness of State-Level Opioid Policies on Opioid-Related Mortality," NBER Working Papers 27029, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:27029
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    References listed on IDEAS

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    Cited by:

    1. Simone Balestra & Helge Liebert & Nicole Maestas & Tisamarie B. Sherry, 2021. "Behavioral Responses to Supply-Side Drug Policy During the Opioid Epidemic," NBER Working Papers 29596, National Bureau of Economic Research, Inc.
    2. Carolina Arteaga Cabrales & Victoria Barone, 2021. "The Opioid Epidemic: Causes and Consequences," Working Papers tecipa-698, University of Toronto, Department of Economics.

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    More about this item

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C54 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Quantitative Policy Modeling
    • H0 - Public Economics - - General
    • H51 - Public Economics - - National Government Expenditures and Related Policies - - - Government Expenditures and Health
    • H7 - Public Economics - - State and Local Government; Intergovernmental Relations
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
    • I28 - Health, Education, and Welfare - - Education - - - Government Policy
    • K32 - Law and Economics - - Other Substantive Areas of Law - - - Energy, Environmental, Health, and Safety Law

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